Bright Simons is the president of mPedigree, a multinational technology and social innovation enterprise operating in several countries in Africa and Asia, known for its anti-counterfeiting, digital supply chain, and agritech platforms and services.

He is also affiliated with IMANI Centre for Policy and Education, a Ghanaian based think-tank, and has served as an Advisor to Microsoft, the World Bank, Care International among others.

Recently, his technical paper published by the Centre for Global Development (CGD), A Farewell to Disruption in a Post-Platform World, drew global attention as it aims to question common narratives such as ‘data is the new oil’ and ‘Big Data is everything’ in a period of rapid technological change.

He spoke to Nation's technology journalist Faustine Ngila about rethinking the concept of disruption as we head to a new decade.

1.   Why do you think the world needs a reality check regarding the use of data?

There has been a substantial growth in awareness about the potential of data to confer power on those who can hoard it. Like all forms of power, data concentration is subject to abuse. Globally, new public institutions are being created to enforce emerging regulations against the abuse of data. That is all well and good. But I choose to focus on another dimension, which is how data acquires the primal potency that makes it convertible to power. It is the dimension of heterogeneity. It is no longer useful to just amass data. You need inter-sectional and multi-sectoral data, often held by very different entities in highly diverse repositories. This bring considerable tension and friction, among values, policies, systems and levels of capacity. The ability to harness data to serve broader public interest, economically valuable, and socially transformative purposes is hampered by this diffuse conflict. In e-health, it has practically halted progress in Africa. The big platforms, like Facebook and Google, are working very hard to navigate these tensions as their artificial intelligence (AI)-based world domination plans are now threatened by the conflict. The amount of resources they need to spend on manual reassembly, sifting, and pruning of data limits the speed at which they can roll out new AI-based services. The automation of these functions are constrained by the current fragmentation. Still, they have far more resources to throw at the problem than local startups, government agencies and development agency – backed NGOs. Unless new alliances are created to back civic and non-corporatist responses to this problem, startup and leapfrogging style innovation in the developing world would be greatly dampened.

2. You mention Christensen’s model as the most practical and useful way to link disruption to the many important areas of socioeconomic development touched by technology. What does it entail?

Actually, my point is that the mechanism Christensen describes as the principal means through which disruption and disruptive innovation happens, despite the harsh criticisms of his theory, is still the most plausible among the competing concepts of disruption. In rough terms, his theory says that it is not sloppiness that makes incumbents (or dominant players in an industry or domain) lose out. Rather, somewhat counter-intuitively, it is getting too good at the things that made them become dominant in the first place. They become so engrossed in maintaining their dominance by refining their initial advantages that they do not pay attention to the changing needs and shifting expectations of customers.

To cling on to their dominance for as long as possible, they keep packing features into their products that add little value, thus reducing the cost-to-utility ratio for their customers, whilst neglecting many potential customers for whom the existing value proposition is too complex, unclear, not affordable or plain confusing. Upstarts come in with simpler and compact alternatives that expand the market by attracting these neglected customers. In time, the upstarts start to win over even the longtime loyal customers of the incumbent/dominant market leader.

Many software-as-a-service companies used similar strategies to break the hold of the big enterprise software vendors like IBM and Oracle. With some modifications here and there, one can even explain the rise of China, Taiwan, South Korea and Malaysia in many global technical industries at the expense of European and American incumbents as having followed a similar paradigm.

One of my key arguments is that whilst the Christensen model explains disruption better than most of its competitors, it is rapidly becoming obsolete. This is due to the fact that the products and services have become so intertwined in how they deliver value to customers that upstarts can often not cheaply and quickly simplify and “compactify” their offerings for differentiated segments of the market in the way they used to be able to do in the earlier days of the technical innovation boom that is now slowing. This spells potentially disastrous news for startups everywhere, but particularly for innovative companies in the developing world with global, or even regional, ambitions.

3. Your paper states that it aims to be a disruptor of comfortable narratives. Which narratives are these?

Several of the current narratives that dominate the headlines of technology, entrepreneurship and innovation essentially, the entire “new economy”coverage and discourse are mismatched with the evolving reality. One of these is that it is becoming easier to consolidate valuable data.

Another is that this data consolidation when harnessed by incredibly powerful algorithms, especially of the machine/deep/reinforcement learning variant (or more broadly, AI), can only make platforms bigger and more dominant over all aspects of our life. Mega-platforms will take over our education, health, transport, defense, logistics, and media. I argue that a few legacy platform companies like Facebook, Google, Microsoft and Amazon will hold out for a bit longer in those areas where they have established serious control over the networks that bind many smaller companies. In mass communications, internet search, basic eCommerce and digital publishing and advertising, their lead shall be unassailable for a while.

But the real reason is less about the power of their algorithms and the quantity of data they have amassed, and more because of the supernodes they have become in webs of integration that now define how nearly all companies collaborate, intertwine, and interlink to deliver value to customers. These legacy mega-platforms enjoy “lattice power” in these hyper-lattices. I call this phenomenon, hyper-integration. Apart from these few legacy platforms and except in the few industries they have sunk their fangs into, most platforms are actually in trouble. Major travel booking sites, entertainment aggregators, and logistics platforms are actually struggling to create value and therefore operate profitably because of the nature of this hyper-integration trend, which is making it harder to manoeuvre within value production and delivery networks.

When it comes to the most important sectors of the economy and domains of society, such as health, education, agriculture and the likes, penetration by mega-platforms will be even more patchy and halting because the heterogeneity of the integrations required compound an already difficult prospect. Thus, it is “integrations” – their maintenance costs, their rigidity, their complexity, their redefinition of risk and fraud  – that is really the dominant factor here, not data or algorithms. In this new world of hyper-integration, disruption is not the primary motif of ascendancy for the vast majority of players, it is “strategic alignment”. I also dispel some popular notions such as the view that block chain is the dominant way of connecting platforms in the future. It is not. It requires a degree of homogeneity that actually goes against current trends.

4. You advocate for techno-legal integration. What does it mean and why do you think it is the right path forward in 2020?

Companies need to understand that their “integrations”, the tools and processes binding them to collaborators and co-innovators with whom they must interface consistently to create and deliver value, are now some of their most critical “assets”. Companies are stuck in a zone where they think of such transactional linkages as primarily “channels”. I argue that integrations should be seen in “asset portfolio” terms. I actually show how African startups with more "polycentric integration" assets grow their investor valuation quicker. A company’s integrations certainly include all the application programming interfaces (APIs) that connect its systems to other systems. But APIs are a very small subset of the full portfolio. The range spans all other critical conjunctions in production processes where consensus among collaborators is required to activate a unit of value. I provide tools in the paper for rating these integrations and managing them properly. I point out however that for startups and most companies in poor countries, the situation is going to be increasingly dire because amassing the right integrations and maintaining them cost money and require skills. Countries that want to see their startups and local companies keen to participate in the new economy thrive should actively consider the “pre-fabrication” of certain key integrations across major social infrastructure and deliver these prefab integrations as “public resources” to enable startups and local companies plug into value creation networks at lower cost and with less friction. Innovation will be stifled in the absence of this “scaffolding”, which I call “hyper-integration operating systems”, or “honeycombs”.

5. You are unimpressed by monocentric integrations and how in the past they have led to unchallenged data consolidation. What are they and how unfavourable are they for African startups?

Mono-integrations are exemplified by the gateways and connection models controlled by the mega-platforms (Facebook, Google, Twitter and the likes) in the digital advertising industry, to cite a prominent example. They are homogeneous; typically dominated by a central rule giver; setup on the basis of highly unbalanced contracts; and designed for higher levels of automation and agile maneuvering. These mono-integrations enabled the data-consolidation that made the current clique of mega-platforms so rich and powerful. They are increasingly not viable as the ongoing “technologisation” of all industries and social domains now expands into areas such as health, agriculture, education, transport, defense, real estate among others. Another integration model, the polycentric, is becoming the only viable approach.

These types of integration among platforms, systems and value chains are heterogenous; designed to work with compromise; accommodate diverging values; enable players with very different economic models and jurisdictional constraints to work with each other. Many incoterms built for global trade often need such integrations to actually function (think of the global freight forwarding industry and how it interconnects). It is harder to consolidate data and use super-algorithms to take over whole industries, as we saw happen in the digital advertising industry, in a polycentric context, such as in much of the healthcare and educational systems. Whilst this trend does slow down the rise and ubiquity of the mega-platforms, they also make it even much harder for startups to replace or displace the mega-platforms. Because Africa is already such a laggard, it is coming late to a party where the rules have changed to frustrate the big boys and girls but without making things any easier for the underdog.

6.    What are the drivers of hyper-integration?

In the paper, I mention several drivers, but I will focus on just three here: fraud, risk and the search for top line growth (hetero-convergence). Digitalisation exacerbates all three. Digital business models are incredibly prone and susceptible to fraud. I give many examples, including the widespread use of GPS spoofing to game location-based services such as Uber. I also mentioned the massive use of bots and other techniques to game digital advertising, with the result that maybe 70 percent of that space is now contaminated with fraud and mistrust.

Other types of risks, including abuse, are also magnified by digitalisation, such as the now widely discussed issues of cyber security. The thing is, having superior data-intelligence or super-algorithms such as mutative anti-viruses are no longer enough to fight fraud and risk. Platforms need to integrate their threat signature databases to be effective. Whether it is fighting spam or malware, standalone systems heavily underperform.

Regarding “top-line” growth, the problem right now is that all the low-hanging fruits for digital have been plucked already: media, telecommunication, mass communication, entertainment, search, social graphing etc. All the big future profits are in areas like health, education, agriculture, defense, transport etc.

7. The sum effect of these drivers is the growing convergence across industries, and the rapid dissolution of boundaries. What does this mean for the world?

For digitalisation to continue to ramp up productivity, some of the underlying economics of industries must converge (hetero-convergence). This requires intense integration of processes to remove some of the efficiency and productivity gaps. These are some of the forces intensifying hyper-integration. The interesting thing is that they reinforce each other. Hetero-convergence deepens risks and the opportunities for fraud, for instance, whilst the need to address both threats accelerates hyper-integration.

8. You mention Lattice Power several times in your paper. What is it and why does it matter?

One of the most fundamental ways in which hyper-integration changes how the new economy game is played and won is how it forces leaders and managers, often without their even realising, to spend more and more of their time, energy, resources and bandwidth, improving their positioning in the hyper-integrated ecosystem, or as I call such ecosystems, “hyper-lattices”. Becoming a super-node in such a lattice gives you “lattice power”. It makes it possible to grow off rents rather than profits, strictly speaking. This can reduce the focus on delighting customers as the primary means of growing market share and improving pricing power through loyalty. There is now evidence that some of the mega-platforms, like Uber, for instance, may even be penalising loyal customers because they can discern who can pay more through "frequent use" analysis. Many airlines are spending time and resources integrating with credit card networks, whilst cutting down on perks in their loyalty programs. They are looking to position themselves within hyper-integrated ecosystems in ways that maximise their ability to extract rent.

9.  So, what does all this mean for technology-entrepreneurship-innovation (TEI)- powered economic development in Africa?

As innovation becomes more expensive and more time-consuming due to the constraints of network politics in the new economy, African innovators, technologists and entrepreneurs cannot seek to grow their enterprises through the harnessing of new ideas and speed to market alone anymore. They must get adept at network politics. Unfortunately, this requires considerable skills and resources not readily available. The long lead-time to profitability implied by the need to amass valuable integrations and to spend time configuring them properly can easily kill off many startups, social enterprises and other new economy aspirants and players in Africa before they get anywhere close to their prime.

Unless a deliberate effort is made to build clever “shared-use” hyper-nodes that innovators can plug into at lower cost, with minimal friction, and in quicker time. These hyper-nodes, or honeycombs, are critical if African new economy players and aspirants are going to take on big challenges in highly polycentric domains and sectors such as health, education, energy, agriculture and transport. Fin-tech is booming because the financial services sector can import whole frameworks for digitalisation much easier. E-commerce has been failing because it interfaces with a larger swathe of polycentric nodes in transport, legal, logistics, consumer education and agent training.

More specialised entrepreneurs and innovators must be incentivised to focus on helping build out these middle-ware integrations that can’t make money directly from end-customers but will be critical for integrated ecosystems to function effectively and reduce the cost, time, and friction of innovation. None of this can begin without a mindset shift and new modes of advocacy, hence my decision to write the paper as part of the CGD series on “technology and development prospects”.